Banking operations are often described as the “back office.” In reality, they are the engine room that powers every transaction, every loan, and every customer interaction. At TD alone, more than 3,000 colleagues across Canada manage functions ranging from credit adjudication to servicing and estate planning.
These are areas where accuracy, speed, and compliance are mission critical. Even small inefficiencies ripple across millions of customers and billions in assets. That is precisely why operations have become the proving ground for AI in financial services.
The combination of high-volume tasks, strict oversight, and rising customer expectations for immediacy makes operations the ideal place for AI to demonstrate measurable impact. As I often say: operations is the frontline where AI proves its value.
How TD Is Using AI to Reimagine Operations
TD has been investing in AI for years, as a strategic capability woven into the business. We’ve moved beyond pilots into live, scalable use cases:
Machine Learning Workforce Planning
Traditional workforce scheduling relies on forecasts that are outdated as soon as they are created. At TD, machine learning continuously learns from transaction patterns, customer behaviors, and seasonal fluctuations.
The result: optimized schedules, more accurate volume predictions, and colleagues cross-skilled to handle peaks and valleys without compromising service levels. For customers, this means shorter wait times and faster service. For employees, it means less burnout and more balanced workloads.
Generative AI Procedure Engine
Maintaining operational procedures has historically been an enormous lift. Every product update or process tweak required rewriting dense documentation. With generative AI, drafting and updating procedures can be cut by more than 85%.
Instead of spending hours rewriting manuals, colleagues validate, refine, and implement improvements. This shift not only drives efficiency but also improves accuracy, governance, and compliance.
Agentic AI in Real Estate Secured Lending (RESL) Adjudication
Mortgage adjudication has long been a time-intensive process. Reviewing documents and validating information could take hours. By deploying agentic AI, these tasks can be done in minutes.
The model reads, validates, and summarizes documents, highlights risks, and allows human reviewers to focus on exceptions. This dramatically accelerates decisions, enhances customer satisfaction, and frees significant capacity within teams.
Taken together, these examples highlight how AI isn’t about replacing people—it’s about equipping them with tools that amplify judgment, precision, and speed.
Empowering People: The Human + Machine Model
A common industry fear is that AI will replace jobs. At TD, our philosophy is different: AI should empower, not replace.
Consider workforce planning. Instead of overwhelming underwriters during volume spikes, AI balances workloads and ensures service levels are met without fatigue. Generative AI tools remove the burden of repetitive writing, giving colleagues more time to apply judgment and creativity. Conversational AI allows employees to access procedures instantly, making them more effective and confident.
To support this, we’ve launched initiatives like the Operations AI Enthusiast Club, where colleagues explore and champion AI use cases, and Copilot training sessions, where employees practice hands-on how AI can assist in their roles.
The result is a workforce that sees AI as an ally, not a threat—a tool for growth, innovation, and career development.
Building Trust: Ethics and Governance in AI
In banking, trust is everything. Customers place not only their money but also their confidence in us. That means every AI-enabled process must be transparent, accountable, and fair.
At TD, our AI governance framework rests on five pillars:
Transparency – Every AI process must remain explainable, with human oversight in decision-making.
Bias Mitigation – Models are trained on diverse datasets and continuously monitored to minimize unintended bias.
Data Security – AI must meet the strictest privacy and cybersecurity standards.
Accountability and Governance – Clear roles, responsibilities, and oversight mechanisms accompany every deployment.
Continuous Monitoring – AI models are tracked and updated to remain effective and relevant.
To accelerate this responsibly, we’ve built cross-functional governance pods—bringing together business, technology, compliance, and risk—so that innovation and compliance move in lockstep.
Balancing innovation with responsibility is not optional. It is how we strengthen, not erode, the trust that underpins financial services.
The Skills of the AI-Enabled Operations Professional
The operations professional of the future will need a dual toolkit:
Technical skills: data literacy, familiarity with machine learning, and the ability to interpret AI outputs.
Human skills: adaptability, critical thinking, ethical judgment, and problem-solving.
It’s not enough to understand what AI says—you must also grasp the why and the so what. That’s why training at TD isn’t only about tools. It’s about building confidence, judgment, and adaptability so our people can thrive in an AI-first workplace.
The Bank of the Future: Fast, Personalized, and Human-Centered
Looking 3–5 years ahead, banking operations will combine automation with empathy:
Generative AI will handle knowledge management, policy drafting, and reporting.
Agentic AI will autonomously manage compliance checks, adjudication, and repetitive workflows.
Machine learning will continuously optimize resources and predict demand.
This future bank will be highly efficient, deeply personalized, and relentlessly customer-focused. Customers will receive decisions in minutes, not days. Employees will spend more time solving complex problems, building deeper relationships, and innovating solutions.
The future is not machine-first—it is human + machine, at scale.
Leadership in the Age of AI
For me personally, working with AI has been transformative. It has made me more data-driven in decisions, more collaborative in solving problems, and more future-focused in strategy.
The legacy I want to leave is simple but powerful: AI-first operations that redefine speed, efficiency, and precision—while keeping ethics, trust, and people at the center.
Just as the internet era reshaped how banks operate, AI is doing it again. We are at the start of a new chapter in financial services—one where operations evolve from a back-office cost center into a strategic driver of growth.
AI in banking operations is no longer optional. It is the foundation of a faster, more human-centered financial system. At TD, we’re proud to show how AI can be transformative—not only for efficiency, but also for trust, empowerment, and customer outcomes.
Continue reading in the FinScale Magazine
This insight was originally published in the first issue of FinScale Magazine by TrialScale. Download the magazine to keep reading.